CAREER: Design of Two-sided Markets In Dynamic and Uncertain Environments: Theoretical and Operational Issues

职业：动态和不确定环境中双边市场的设计：理论和操作问题

• 批准号: 1351821
• 负责人: Mustafa Akan
• 金额: $ 40.06万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-02-01 至 2019-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1351821&HistoricalAwards=false
• 关键词: CAREER; Design; Two; sided; Markets; CAREER; Design; Two; sided; Markets

The research objective of this Faculty Early Career Development (CAREER) Program award is to study the design of two-sided markets in dynamic and uncertain settings. The population of agents in the system evolves over time due to stochastic arrivals to both sides of the market. Agents report their preferences upon entering the system, and either accept or reject match offers based on the compatibility of preferences as well as value of future options. The primary goal of this award is to design such marketplaces in an efficient way by taking into account dynamic interaction, uncertainty and forward looking behavior of agents. The research approach is to compute each agent's expected benefit from remaining unmatched as a utility promise from the market designer under a given policy, which will enable an algorithm for (dynamically) individually-rational match offers. The algorithm will be generalized to the environment where agents may not know their true preferences over matches before the match and there are multiple matches generated on both sides. Further analysis will endow agents with straightforward incentives for truthful behavior and consider the possibility that a market designer learns about agent preferences by observing their responses to match offers while the agents learn about the distribution of available partners by observing the offers they get.If successful, the results of this research will lead to improvements in the layout of markets where there is a need to match two-sided populations of agents such as labor markets, organ transplant, child adoption, and foster care. The award can provide modeling and analysis tools to maximize the efficiency of the matching system and the welfare of its participants. The research is made possible by combining tools developed both in matching/market design in economics and those commonly used in operations. The mathematics developed will also help train graduate and undergraduate students as well as contribute to an ongoing private public partnership between Carnegie Mellon and Pennsylvania Adoption Exchange (PAE).

该教师早期职业发展（职业）计划奖的研究目标是研究动态和不确定环境中双面市场的设计。由于随机到达市场的两侧，系统中的代理人的人口随着时间的流逝而演变。代理商报告他们进入系统时的偏好，并根据偏好的兼容性以及未来选项的价值接受或拒绝匹配报价。该奖项的主要目标是通过考虑动态互动，不确定性和前瞻性行为来以有效的方式设计此类市场。研究方法是根据给定政策在市场设计师中保持无与伦比的承诺来计算每个代理商的预期收益，这将为（动态）单独理性的匹配提供的算法提供算法。该算法将概括为代理在比赛前可能不知道其真正偏好的环境，并且双方都有多个匹配项。进一步的分析将赋予代理人对真实行为的直接激励措施，并考虑市场设计师通过观察他们对匹配报价的反应来学习代理偏好的可能性，而代理人通过观察他们获得的报价来了解可用合作伙伴的分布。关心。该奖项可以提供建模和分析工具，以最大程度地提高匹配系统的效率及其参与者的福利。通过组合在经济学的匹配/市场设计和运营中使用的工具中开发的工具，从而实现了这项研究。开发的数学还将有助于培训毕业生和本科生，并为卡内基·梅隆（Carnegie Mellon）和宾夕法尼亚州收养交易所（PAE）之间的持续私人公共伙伴关系做出贡献。